Automated PP-PME (task) load-balancing: balancing non-bonded force and PME mesh workload when the two are executed on different compute-resources (i.e CPU and GPU or different CPUs). This enables GPU-CPU and PP-PME process load balancing by shifting work from the mesh to the non-bonded calculation.

PPPM/P3M with analytical derivative at the same cost and with the same features as PME.

New, advanced free energy sampling techniques.

Build configuration now uses CMake, configure+autoconf/make no longer supported. (The CMake build system features with a lot of automation and cleverness under the hood and we know that the it might not always prove to be as rock-solid as the old one. However, far more advanced and complex, so bare with us while we iron out issues that come up along the way.)

Bugfixes

No critical bugfixes. All important fixes are also present in 4.5.6 and documented there.

Changes that might affect your results

None for simulations set up with the traditional group cut-off scheme.

When switching from the group scheme to the Verlet scheme, simulations can get more accurate due to the exact cut-off treatment and buffering (this will, of course, depend on the original cut-off settings used). See the section Cut-off schemes for details.

Other important changes compared to 4.5

mdrun does now thread affinity setting by deafult

This means that when runing multiple mdrun processes on the same machine, one has to either provide a core "pin offset" using the -pinoffset command line option, or turn off internall affinities and take the performance hit (or alternatively manage affinities externally).

The choice of compiler matters more

With the switch to SIMD intrinsics, up-to-date SIMD CPU acceleration support, OpenMP, the compiler used matters more, both in terms of performance and ability to compile GROMACS correctly. The recommended compilers that are known to work (=compile GROMACS correctly) and provide good performance on x86/AMD64 are gcc 4.5 and later, Intel Compilers 12.0 and clang 3.1 (note the lack of OpenMP support which can cause 30%+ performance loss). For further details see ???.